Building Subconscious Processing in AGI

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Human Subconsciousness

Subconscious processing is a fundamental aspect of human intuition, allowing individuals to store and retrieve vast amounts of information effortlessly. The term "subconscious" refers to the part of the mind that operates below the level of conscious awareness, continuously processing sensory inputs, memories, and learned experiences. This processing enables quick, automatic responses to familiar situations and contributes to our ability to make intuitive decisions.

In humans, the subconscious mind is described as the mental activities just below the threshold of consciousness. It is a reservoir of near unlimited capacity, storing information about every experience we have ever had, even though we are not actively aware of this information. This stored data influences our perceptions, behaviors, and decisions, often without us realizing it. The subconscious is responsible for pattern recognition, identifying and interpreting recurring sequences without deliberate thought, forming the basis for gut feelings or hunches based on past experiences and learned associations.

For AGI to develop similar capabilities, it would need an AI system that combines an autoregressive model, such as a GPT-based Large Language Model (LLM), with a fast knowledge graph. This combination would store experiences in a way similar to humans and retrieve them efficiently. This system would enable the AGI to learn from past interactions, adapt to new situations seamlessly, and draw from a deep well of accumulated knowledge when making decisions.

Neural Architectures and Background Processing

GPT-based LLMs can be used to mimic such human subconscious processing in a simplified way. By leveraging autoregressive capabilities, GPT models can generate contextually relevant outputs based on previous data, effectively simulating the way the human subconscious mind processes information in the background.

GPT-based LLMs can be used to continuously process and analyze incoming information such as interactions with the environment, updating their internal models to reflect new information and interactions. This continuous processing allows the AGI to develop an internal model of its external environment, akin to the human subconscious mind. The models are trained on diverse datasets, encompassing a wide range of scenarios and contexts, enabling them to draw from a broad base of knowledge when making decisions.

Associative Learning and Memory Systems

Additionally, the AGI’s memory system should support associative learning, where it can form connections between different pieces of information. This would allow the AGI to draw on past experiences to inform its decisions, even in novel situations. For instance, if an AGI encounters a new task that resembles a previously learned task, it can leverage its subconscious processing to apply relevant knowledge and make intuitive judgments.

Implementing mechanisms for long-term and short-term memory in AGI can enhance its subconscious processing. Long-term memory would store extensive knowledge accumulated over time, while short-term memory would handle immediate, transient information. Together, these memory systems would enable the AGI to access and utilize information effectively, mirroring the way the human brain integrates subconscious processing with conscious thought.

See Human Memory & LLM Efficiency: Optimized Learning through Temporal Memory.

By developing these memory and GPT-based LLMs models with temporal information, AGI can achieve a level of subconscious processing. It can enable intuitive understanding that approximates human intuition to create AGI that can navigate complex environments and make informed decisions with a level of spontaneity and depth akin to human intuitive thought.

Further read

LLM, Us and Neuroplasticity

"Are you sure?": Unveiling the Quest for Human-Like Artificial Intelligence

Designers, creativity and AI

A LLM as a reflection of our inner most desires

Should AGI be a she, he, or a it?